Overview: The laboratory has established research methodology and protocols, built an infrastructure of hardware and software, formed collaborative arrangements, trained a team of scientists and support personnel to utilize the methodology of RNA-Seq. We have performed over 250 sequencing runs on the Illumina HiSeq 2000 and obtained over 20 billion reads of transcriptome sequence information. Consequently, the main effort of the past year was devoted to intensive analysis of the resulting datasets. We have sequenced the transcriptomes of physiologically or genetically labeled pain-sensing neurons sorted by FACS, neurons in dorsal spinal cord during peripheral inflammation, models of rheumatoid arthritis, inflamed peripheral tissue, axotomized DRG and dorsal and ventral spinal cords and periphera nerve. In many cases multiple time points were sampled to follow the evolution and resolution of the intervention with enough samples at each point to permit statistical comparison. Because we sorted for certain neuronal populations we know which genes are in the pain-sensing neurons and which are in mainly non-pain-sensing neurons such as proprioceptive primary afferents and glial cells. The ability to form incisive hypotheses regarding pain physiology is greatly advanced by this type of tissue and neuron-specific information. We now have quantitative information on all the genes that mediate DRG and sensory and motor spinal cord functions. TRPV1 Transcriptome: One important focus of the neuronal sorting experiments is a particular subpopulation of DRG neurons that express a multifunctional thermo- chemo- pH- and lipid-responsive ion channel called TRPV1. This ion channel is also gated by capsaicin, the active ingredient in hot pepper. Previous experiments demonstrated that the potent capsaicin analog resiniferatoxin (RTX) can control cancer pain in dogs and humans. Because of this crucial role in pain transmission, we want to know everything possible about TRPV1-expressing DRG neurons. We isolated TRPV1 neurons by genetic labeling or physiological activation and then performed deep sequencing of the mRNA content using next-gen RNA-Seq. The genetic method expresses a fluorescent marker allowing the TRPV1 DRG neurons to be isolated by FACS. A second strategy was to load primary DRG neurons with a calcium sensitive dye, stimulate them with RTX and sort the neurons that display RTX-induced increases in fluorescence. We also killed the cells either genetically or by microinjection of RTX. Our first paper (in press) outlines the transcriptome results from the genetically labeled TRPV1 neurons and ganglia in which the TRPV1 neurons had been deleted by expression of diphtheria toxin or microinjection of RTX. This has provided comprehensive, new transcriptomic information on genes expressed by a clinically important population of nociceptive neurons. Analgesia transcriptome: One of the most interesting aspects of the transcriptome analyses is quantitative insight provided by next-gen RNA-Seq. We now know the quantitative relationships between the exact genes that mediate the actions of known analgesic drugs such as morphine, clonidine, lidocaine, ibuprofen, and gabapentin. It has not been clear which paralogs or subunits of drug binding receptors are expressed by different tissues in the pain pathway, yet this becomes clear when expression values for all the relevant genes are obtained quantitatively, at the same time, and with excellent reproducibility between animals and treatments. Additional analgesic targets: The transcriptome experiments also point to new targets for potential analgesic drug development. An example is an orphan GPCR, although its analgesic potential has not been explored. In another example, we observe that the Mu opioid receptor is mainly expressed in the DRG and less so in dorsal spinal cord. This allows us to conclude that epidural or intrathecal opioid analgesia is mainly mediated by a presynaptic actions on DRG neurons and provides a framework for peripheral nervous system therapeutic strategies. Amplification of ongoing studies: The RNA-Seq results also inform and amplify hypothesis-driven studies from our and other groups. In a collaborative work with NIAAA, we observe that certain lipids are TRPV1 agonists. Using the transcriptome databases, we extracted the quantitative expression data for all the genes involved in lipid transport, generation, degradation, and the cognate receptors for the relevant lipids from sequencing of skin, DRG and dorsal spinal cord. Differential expression levels therein provided insight into new enzymes that generate particular lipids important for TRPV1 activation. Canine ganglionic transcriptome: This year we completed the canine tissue collection for the cancer pain transcriptome study. Ganglion and spinal cord tissue have been obtained from controls and animals with osteosarcoma that were euthanized because of inadequate pain control or treated with resiniferatoxin. Tissues were obtained at autopsy. This study was undertaken to test for genes activated by nociceptive input from naturally occurring bone cancer and modulated by treatment. This will form a unique dataset that will provide new insight into the transcriptomics of cancer pain in a species with a cancer pain problem that is very similar to the human. Cross-species comparison: Another project we are in the process of completing is a species comparison of DRG and trigeminal ganglia and dorsal spinal cord transcriptomes. Initial comparisons show several remarkable species differences in degree of expression. This study is providing a new level of cross-species validation of potential therapeutic targets and mechanisms that aid in ascertaining the predictive capability of translational animal models. Summary: The datasets acquired over the past year provide unprecedented and extremely fine grained detail on gene expression in pain sensing circuits. This may seem complicated but the basic goal is to understand how we sense pain and how we may control it when necessary. There are a wide variety of painful stimuli that can be encountered in our environment and different neurons exist to sense these different types of pain signals. We are trying to figure out exactly what molecules the different types of pain-sensing neurons make and how they work together to do their job. We will use this information to understand pain signaling and how to control it. Taken together these data will provide a transformative new resource for the pain research community and will allow a new, much more precise assessment of experimental manipulations and verification of experimental results.